datafog 3.1.0b1

Scan, redact, and manage PII in your documents before they get uploaded to a Retrieval Augmented Generation (RAG) system.

Open-source DevSecOps for Generative AI Systems.

Overview

What is DataFog?

DataFog is an open-source DevSecOps platform that lets you scan and redact Personally Identifiable Information (PII) out of your Generative AI applications.

Core Problem

How do you keep:

• Customer PII
• Employee PII
• Sensitive company information pertaining to org changes or restructurings
• Pending M&A activity
• Conversations with external counsel on material corporate matters (i.e. product recall, etc)
• and more

from entering a Generative AI environment in the first place? What you need is a tool to scan and redact your RAG-bound documents based on your organization or team needs.

That's where DataFog comes in.

How it works

There's lots of PII tools out there; why DataFog?

If you look at the landscape of PII detection tools, their very existence was in many cases driven by regulatory requirements (i.e. 'comply with CCPA/GDPR/HIPAA'). In this scenario, there's a very defined problem, a specific set of immutable entities to look for, and a relatively static universe of document schema to work with. What that means as an end-result is that the products are purpose-built for the problem that they are solving.

However, Generative AI changes how we think about privacy. There's now a changing set of privacy requirements (new M&A deals, internal discussions means new terms to scan/redact) as well as different and varying document sources to contend with. PII detection is no longer just about compliance, it's an active - and for some, new - internal security threat for CISOs and Eng Leaders to contend with. We want DataFog to be built and driven to meet the needs of the open-source community as they tackle this challenge.

Roadmap

DataFog is an active project with regular weekly releases to production (typically on/around Monday evenings US PT). Here's a snapshot of our coming roadmap; if you have questions or would like to weigh in, join our discord and let us know what we can do to make the product better!

Installation

DataFog can be installed via pip:

pip install datafog

Examples - Updated for v3

Check out for examples to get started with datafog v3: https://colab.research.google.com/drive/1k3HPaOTur3iDfBdWXh7O_EjzsjI_K6wT#scrollTo=WNtUZ497_0kd

Contributing

DataFog is a community-driven open-source platform and we've been fortunate to have a small and growing contributor base. We'd love to hear ideas, feedback, suggestions for improvement - anything on your mind about what you think can be done to make DataFog better! Join our Discord and join our growing community.

Dev Notes

• Justfile commands:
  • just format to apply formatting.
  • just lint to check formatting and style.

Testing

To run the datafog unit tests, check out this repository and do

tox

License

This software is published under the MIT license.